Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userStructural propagation in a production network with restoring substitution elasticities
87
0
0.0
(
0
)
Added by
Kazuhiko Nishimura
Publication date
2017
fields
Financial
and research's language is
English
Ask ChatGPT about the research
No Arabic abstract
We model an economy-wide production network by cascading binary compounding functions, based on the sequential processing nature of the production activities. As we observe a hierarchy among the intermediate processes spanning the empirical input--output transactions, we utilize a stylized sequence of processes for modeling the intra-sectoral production activities. Under the productivity growth that we measure jointly with the state-restoring elasticity parameters for each sectoral activity, the network of production completely replicates the records of multi-sectoral general equilibrium prices and shares for all factor inputs observed in two temporally distant states. Thereupon, we study propagation of a small exogenous productivity shock onto the structure of production networks by way of hierarchical clustering.
rate research
Read More
We measure elasticity of substitution between foreign and domestic commodities by two-point calibration such that the Armington aggregator can replicate the two temporally distant observations of market shares and prices. Along with the sectoral multifactor CES elasticities which we estimate by regression using a set of disaggregated linked input--output observations, we integrate domestic production of two countries, namely, Japan and the Republic of Korea, with bilateral trade models and construct a bilateral general equilibrium model. Finally, we make an assessment of a tariff elimination scheme between the two countries.
We analyze export data aggregated at world global level of 219 classes of products over a period of 39 years. Our main goal is to set up a dynamical model to identify and quantify plausible mechanisms by which the evolutions of the various exports affect each other. This is pursued through a stochastic differential description, partly inspired by approaches used in population dynamics or directed polymers in random media. We outline a complex network of transfer rates which describes how resources are shifted between different product classes, and determines how casual favorable conditions for one export can spread to the other ones. A calibration procedure allows to fit four free model-parameters such that the dynamical evolution becomes consistent with the average growth, the fluctuations, and the ranking of the export values observed in real data. Growth crucially depends on the balance between maintaining and shifting resources to different exports, like in an explore-exploit problem. Remarkably, the calibrated parameters warrant a close-to-maximum growth rate under the transient conditions realized in the period covered by data, implying an optimal self organization of the global export. According to the model, major structural changes in the global economy take tens of years.
The major perspective of this paper is to provide more evidence into the empirical determinants of capital structure adjustment in different macroeconomics states by focusing and discussing the relative importance of firm-specific and macroeconomic characteristics from an alternative scope in U.S. This study extends the empirical research on the topic of capital structure by focusing on a quantile regression method to investigate the behavior of firm-specific characteristics and macroeconomic variables across all quantiles of distribution of leverage (total debt, long-terms debt and short-terms debt). Thus, based on a partial adjustment model, we find that long-term and short-term debt ratios varying regarding their partial adjustment speeds; the short-term debt raises up while the long-term debt ratio slows down for same periods.
A favorable population schedule for the entire potential human family is sought, under the overlapping generations framework, by treating population (or fertility) as a planning variable in a dynamical social welfare maximization context. The utilitarian and maximin social welfare functions are examined, with zero future discounting, while infinity in the maximand is circumvented by introducing the depletion of energy resources and its postponement through technological innovations. The model is formulated as a free-horizon dynamical planning problem, solved via a non-linear optimizer. Under exploratory scenarios, we visualize the potential trade-offs between the two welfare criteria.
We study adaptive learning in a typical p-player game. The payoffs of the games are randomly generated and then held fixed. The strategies of the players evolve through time as the players learn. The trajectories in the strategy space display a range of qualitatively different behaviors, with attractors that include unique fixed points, multiple fixed points, limit cycles and chaos. In the limit where the game is complicated, in the sense that the players can take many possible actions, we use a generating-functional approach to establish the parameter range in which learning dynamics converge to a stable fixed point. The size of this region goes to zero as the number of players goes to infinity, suggesting that complex non-equilibrium behavior, exemplified by chaos, may be the norm for complicated games with many players.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
